Cambridge University Press, Date: 1998-07-28. paperback. Good. 7x0x10. 1998. Cambridge University Press ISBN 0521633966 9780521633963 [US]

Paperback. Very Good. ISBN 0521633966 9780521633963 [GB]

Cambridge Cambridge University Press 1998 Trade paperback Good. Trade paperback (US). Contains: Line drawings. Cambridge Series in Statistical and Probabilistic Mathematics . 20 b/w illus. Intended for professional and scholarly audience. May show signs of wear, highlighting, writing, and previous use. This item may be a former library book with typical markings. No guarantee on products that contain supplements Your satisfaction is 100% guaranteed. Twenty-five year bookseller with shipments to over fifty million happy customers.

Cambridge University Press. paperback. Like New. 6x0x8. Looks unread with ownership ink to the title page. Please email for photos. Cambridge University Press ISBN 0521633966 9780521633963 [US]

ISBN10: 0521633966, ISBN13: 9780521633963, [publisher: Cambridge University Press] Softcover
[Columbia, MD, U.S.A.] [Publication Year: 1998]
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Cambridge Cambridge University Press 1998 Trade paperback New. Trade paperback (US). Contains: Line drawings. Cambridge Series in Statistical and Probabilistic Mathematics . 20 b/w illus. Intended for professional and scholarly audience.

ISBN10: 0521633966, ISBN13: 9780521633963, [publisher: Cambridge University Press] Softcover Druck auf Anfrage Neuware - Printed after ordering - For students in pure and applied probability; lots of applications, fairly self-contained.
[Einbeck, Germany] [Publication Year: 1998]
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Paperback / softback. New. A textbook for students with some background in probability that develops quickly a rigorous theory of Markov chains and shows how actually to apply it, e.g. to simulation, economics, optimal control, genetics, queues and many other topics, and exercises and examples drawn both from theory and practice. ISBN 0521633966 9780521633963 [GB]

ISBN10: 0521633966, ISBN13: 9780521633963, [publisher: Cambridge University Press] Softcover Druck auf Anfrage Neuware - Printed after ordering - For students in pure and applied probability; lots of applications, fairly self-contained.
[Einbeck, Germany] [Publication Year: 1998]
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Cambridge Cambridge University Press 1998 Trade paperback New. Trade paperback (US). 254 p. Cambridge Series in Statistical and Probabilistic Mathematics . 20 Line drawings, unspecified. Intended for professional and scholarly audience.

ISBN10: 0521633966, ISBN13: 9780521633963, [publisher: Cambridge Univ Pr] Softcover 237 pages. 10.00x7.25x1.00 inches. In Stock.
[Exeter, United Kingdom] [Publication Year: 1998]

Cambridge University Press, Date: 1998-07-28. Paperback. New. New. In shrink wrap. Looks like an interesting title! 1998. Cambridge University Press ISBN 0521633966 9780521633963 [US]

Cambridge University Press. New. Special order direct from the distributor Cambridge University Press ISBN 0521633966 9780521633963 [CA]

ISBN10: 0521633966, ISBN13: 9780521633963, [publisher: Cambridge University Press, Cambridge] Softcover Paperback. Markov chains are central to the understanding of random processes. This is not only because they pervade the applications of random processes, but also because one can calculate explicitly many quantities of interest. This textbook, aimed at advanced undergraduate or MSc students with some background in basic probability theory, focuses on Markov chains and quickly develops a coherent and rigorous theory whilst showing also how actually to apply it. Both discrete-time and continuous-time chains are studied. A distinguishing feature is an introduction to more advanced topics such as martingales and potentials in the established context of Markov chains. There are applications to simulation, economics, optimal control, genetics, queues and many other topics, and exercises and examples drawn both from theory and practice. It will therefore be an ideal text either for elementary courses on random processes or those that are more oriented towards applications. In this rigorous account the author studies both discrete-time and continuous-time chains. A distinguishing feature is an introduction to more advanced topics such as martingales and potentials, in the established context of Markov chains. There are applications to simulation, economics, optimal control, genetics, queues and many other topics, and a careful selection of exercises and examples drawn ...